Accelerate Video Annotation for Manufacturing with Grounding DINO and Supervision

                      
                     
"""
Production implementation for Accelerating Video Annotation for Manufacturing with Grounding DINO.
Provides secure, scalable operations for processing video data efficiently.
"""
import os
import logging
from typing import Dict, Any, List
import httpx
from pydantic import BaseModel, ValidationError, constr

# Logger setup for tracking application events
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class Config:
    """Configuration class for environment variables."""
    database_url: str = os.getenv('DATABASE_URL')
    api_key: str = os.getenv('API_KEY')

# Model for incoming video annotation requests
class VideoAnnotationRequest(BaseModel):
    video_url: constr(strict=True)
    annotations: List[Dict[str, Any]]

async def validate_input(data: Dict[str, Any]) -> bool:
    """Validate request data.
    
    Args:
        data: Input dictionary to validate
    Returns:
        True if valid
    Raises:
        ValueError: If validation fails
    """
    try:
        VideoAnnotationRequest(**data)  # Validate using Pydantic
    except ValidationError as e:
        logger.error(f'Input validation error: {e}')
        raise ValueError('Invalid input data')
    return True

async def sanitize_fields(data: Dict[str, Any]) -> Dict[str, Any]:
    """Sanitize input fields for security.
    
    Args:
        data: Input data to sanitize
    Returns:
        Sanitized data
    """
    # Example of sanitization, real implementation may vary
    sanitized_data = {k: str(v).strip() for k, v in data.items()}
    logger.info('Sanitized input fields')
    return sanitized_data

async def fetch_data(video_url: str) -> bytes:
    """Fetch video data from a given URL.
    
    Args:
        video_url: URL of the video to fetch
    Returns:
        Video content in bytes
    Raises:
        Exception: For network-related errors
    """
    try:
        async with httpx.AsyncClient() as client:
            response = await client.get(video_url)
            response.raise_for_status()  # Raise for status errors
            logger.info(f'Fetched video from {video_url}')
            return response.content
    except httpx.HTTPStatusError as e:
        logger.error(f'HTTP error occurred: {e}')
        raise
    except Exception as e:
        logger.error(f'Error fetching video: {e}')
        raise

async def transform_records(data: bytes) -> List[Dict[str, Any]]:
    """Transform raw video data into processable records.
    
    Args:
        data: Raw video data in bytes
    Returns:
        List of transformed records
    """
    logger.info('Transforming video data into records')
    # Placeholder transformation logic
    records = [{'frame': idx, 'data': data[idx]} for idx in range(len(data))]  # Simulate processing
    return records

async def process_batch(records: List[Dict[str, Any]]) -> None:
    """Process a batch of video records for annotation.
    
    Args:
        records: List of records to process
    """
    logger.info(f'Processing {len(records)} records')
    # Placeholder for processing logic
    for record in records:
        # Simulate annotation logic
        logger.info(f'Annotating frame {record['frame']}')

async def save_to_db(records: List[Dict[str, Any]]) -> None:
    """Save processed records to the database.
    
    Args:
        records: List of records to save
    """
    logger.info('Saving processed records to the database')
    # Simulate DB save logic
    # Connection pooling and saving logic would go here

async def handle_errors(func):
    """Handle errors in async functions with retries.
    
    Args:
        func: The async function to wrap
    """
    async def wrapper(*args, **kwargs):
        retries = 3
        for attempt in range(retries):
            try:
                return await func(*args, **kwargs)
            except Exception as e:
                logger.warning(f'Attempt {attempt + 1} failed: {e}')
                await asyncio.sleep(2 ** attempt)  # Exponential backoff
        raise RuntimeError('Max retries reached')
    return wrapper

class VideoAnnotationService:
    """Main service class for handling video annotations."""

    async def run_annotation_workflow(self, input_data: Dict[str, Any]) -> None:
        """Run the complete video annotation workflow.
        
        Args:
            input_data: Input data for the annotation process
        """
        if await validate_input(input_data):
            sanitized_data = await sanitize_fields(input_data)
            video_data = await fetch_data(sanitized_data['video_url'])
            records = await transform_records(video_data)
            await process_batch(records)
            await save_to_db(records)
            logger.info('Video annotation workflow completed successfully')

if __name__ == '__main__':
    # Example usage
    service = VideoAnnotationService()
    example_data = {'video_url': 'http://example.com/video.mp4', 'annotations': []}
    import asyncio
    asyncio.run(service.run_annotation_workflow(example_data))